228 resultados para GENERAL CORRELATION
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Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve.
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Measurements were made of the intake of a WHO/UNICEF glucose-based and a rice cereal-based oral rehydration solution (ORS) by children with diarrhoea. Twenty children who presented to the Children's Outpatient Department at Port Moresby General Hospital with acute diarrhoea and mild dehydration were randomly assigned to an ORS and measurements were taken over the following 3 hours. For data analysis, the patients were paired by weight. Testing the means of the paired samples by t test showed that there was no significant difference between the amount of rice ORS and the amount of glucose ORS taken over 3 hours. The discovery of oral rehydration solution (ORS) for the treatment of diarrheal disease has been heralded as the most important medical discovery of the century. Cereal-based ORS is able to decrease stool output and the duration of diarrheal illness more than the standard glucose-based ORS, through the increased absorption provided by oligosaccharides without the imposition of a greater osmotic penalty. Moreover, the peptides in cereals enhance amino acid and water absorption, while providing nutritional benefits. UNICEF's glucose-based ORS is becoming more widely used in Papua New Guinea (PNG). 20 children aged 6-37 months (mean age, 15 months) who presented to the Children's Outpatient Department at Port Moresby General Hospital during September-October 1993 with acute diarrhea and mild dehydration were randomly assigned to receive either a rice-based ORS or standard glucose ORS, and measurements were taken over the following 3 hours. The patients were paired by weight for analysis. No statistically significant difference was found between the amount of rice ORS and the amount of glucose ORS taken over 3 hours.
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The guardians of children brought to the Port Moresby General Hospital's Children's Outpatient Department with a chief complaint of diarrhoeal disease were questioned regarding their preference of glucose-based vs rice-based oral rehydration solution (ORS) in order to determine the acceptability of a rice-based ORS. Of the 93 guardians interviewed, greater than 60% preferred the glucose-based solution in its mixability, appearance and taste, and 65% initially reported that their children preferred the taste of the glucose solution. However, after a 30-minute trial, only 58% of children still preferred the glucose solution. In a country where diarrhoeal disease is a leading cause of child death and guardians are the primary health care providers, the acceptability of an ORS is critical to the morbidity and mortality of Papua New Guinea's children. Killing an estimated 2.9 million children annually, diarrheal disease is the second leading cause of child mortality worldwide. Diarrheal disease is also the second leading cause of child mortality in Papua New Guinea (PNG), killing an average 193 inpatient children per year over the period 1984-90. However, despite the high level of diarrhea-related mortality and the proven efficacy of oral rehydration therapy (ORT) in managing diarrhea-related dehydration, standardized ORT has been underutilized in PNG. The current glucose-based oral rehydration solution (ORS) does not reduce the frequency or volume of a child's diarrhea, the most immediate concern of caregivers during episodes of illness. Cereal-based ORS, made from cereals which are commonly available as food staples in most countries, better address the short-term concerns of caregivers while offering a superior nutritional profile. A sample of guardians of children brought to the Port Moresby General Hospital's Children's Outpatient Department complaining of child diarrhea were asked about their preferences on glucose-based versus rice-based ORS in order to determine the acceptability of a rice-based ORS. More than 60% of the 93 guardians interviewed preferred the glucose-based solution for its mixability, appearance, and taste. 65% initially reported that their children preferred the taste of the glucose solution. However, after a 30-minute trial, only 58% of children still preferred the glucose solution.
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The New South Wales Attorney-General and Justice Policy Division released a Discussion Paper about reform of the Limitation of Actions Act 1969. The key question was whether and how to amend the statute to better provide access to justice for civil claimants in child abuse cases. This submission draws on published literature and multidisciplinary research to support the Discussion Paper's Option A, namely, to abolish the time limit for civil claims for injuries in criminal child abuse cases, and for this to be made retrospective.
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Aim There are limited studies documenting the frequency and reason for attendance to primary health care services in Australian children, particularly for urban Aboriginal and Torres Strait Islander children. This study describes health service utilisation in this population in an urban setting. Methods An ongoing prospective cohort study of Aboriginal and Torres Strait Islander children aged <5 years registered with an urban Aboriginal and Torres Strait Islander primary health care centre in Brisbane, Australia. Detailed demographic, clinical, health service utilisation and risk factor data are collected by Aboriginal researchers at enrolment and monthly for a period of 12 months on each child. The incidence of health service utilisation was calculated according to the Poisson distribution. Results Between 14 February 2013 and 31 October 2014, 118 children were recruited, providing data for 535 child-months of observation. Ninety-one percent of children were Aboriginal, 4% Torres Strait Islander and 5% were both Aboriginal and Torres Strait Islander. The incidence of presentations to see a doctor for any reason was 43.9 episodes/100 child months (95%CI 38.4 – 49.9) The most common reasons for presentation were for immunisations (23%), respiratory illnesses (19%) and for Australian Government funded Indigenous child health check (16%). The primary health services used, for majority of these visits were Aboriginal and Torres Strait Islander specific medical services (61%). Conclusions Within a cultural-specific service for an urban Aboriginal and Torres Strait Islander people, there is a high frequency of childhood attendance at for primary health care services. Well-health checks and respiratory illnesses were the most common reasons. The high proportion of visits for well child services suggests a potential for opportunistic health promotion, education and early interventions across a range of child health issues.
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BACKGROUND AND PURPOSE Inflammation is a recognized risk factor for the vulnerable atherosclerotic plaque. The study explores the relationship between the degree of Magnetic Resonance (MR)"defined inflammation using Ultra Small Super-Paramagnetic Iron Oxide (USPIO) particles and the severity of luminal stenosis in asymptomatic carotid plaques. METHODS Seventy-one patients with an asymptomatic carotid stenosis of ĝ‰¥40% underwent multi-sequence USPIO-enhanced MR imaging. Stenosis severity was measured according to the NASCET and ECST methods. RESULTS No demonstrable relationship between inflammation as measured by USPIO-enhanced signal change and the degree of luminal stenosis was found. CONCLUSIONS Inflammation and stenosis are likely to be independent risk factors, although this needs to be further validated.
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Objective: The aim of this study was to explore whether there is a relationship between the degree of MR-defined inflammation using ultra small super-paramagnetic iron oxide (USPIO) particles, and biomechanical stress using finite element analysis (FEA) techniques, in carotid atheromatous plaques. Methods and Results: 18 patients with angiographically proven carotid stenoses underwent multi-sequence MR imaging before and 36 h after USPIO infusion. T2 * weighted images were manually segmented into quadrants and the signal change in each quadrant normalised to adjacent muscle was calculated after USPIO administration. Plaque geometry was obtained from the rest of the multi-sequence dataset and used within a FEA model to predict maximal stress concentration within each slice. Subsequently, a new statistical model was developed to explicitly investigate the form of the relationship between biomechanical stress and signal change. The Spearman's rank correlation coefficient for USPIO enhanced signal change and maximal biomechanical stress was -0.60 (p = 0.009). Conclusions: There is an association between biomechanical stress and USPIO enhanced MR-defined inflammation within carotid atheroma, both known risk factors for plaque vulnerability. This underlines the complex interaction between physiological processes and biomechanical mechanisms in the development of carotid atheroma. However, this is preliminary data that will need validation in a larger cohort of patients.
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High resolution, USPIO-enhanced MR imaging can be used to identify inflamed atherosclerotic plaque. We report a case of a 79-year-old man with a symptomatic carotid stenosis of 82%. The plaque was retrieved for histology and finite element analysis (FEA) based on the preoperative MR imaging was used to predict maximal Von Mises stress on the plaque. Macrophage location correlated with maximal predicted stresses on the plaque. This supports the hypothesis that macrophages thin the fibrous cap at points of highest stress, leading to an increased risk of plaque rupture and subsequent stroke.
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Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.
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Selection criteria and misspecification tests for the intra-cluster correlation structure (ICS) in longitudinal data analysis are considered. In particular, the asymptotical distribution of the correlation information criterion (CIC) is derived and a new method for selecting a working ICS is proposed by standardizing the selection criterion as the p-value. The CIC test is found to be powerful in detecting misspecification of the working ICS structures, while with respect to the working ICS selection, the standardized CIC test is also shown to have satisfactory performance. Some simulation studies and applications to two real longitudinal datasets are made to illustrate how these criteria and tests might be useful.
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This paper proposes a linear quantile regression analysis method for longitudinal data that combines the between- and within-subject estimating functions, which incorporates the correlations between repeated measurements. Therefore, the proposed method results in more efficient parameter estimation relative to the estimating functions based on an independence working model. To reduce computational burdens, the induced smoothing method is introduced to obtain parameter estimates and their variances. Under some regularity conditions, the estimators derived by the induced smoothing method are consistent and have asymptotically normal distributions. A number of simulation studies are carried out to evaluate the performance of the proposed method. The results indicate that the efficiency gain for the proposed method is substantial especially when strong within correlations exist. Finally, a dataset from the audiology growth research is used to illustrate the proposed methodology.
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A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.
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Selecting an appropriate working correlation structure is pertinent to clustered data analysis using generalized estimating equations (GEE) because an inappropriate choice will lead to inefficient parameter estimation. We investigate the well-known criterion of QIC for selecting a working correlation Structure. and have found that performance of the QIC is deteriorated by a term that is theoretically independent of the correlation structures but has to be estimated with an error. This leads LIS to propose a correlation information criterion (CIC) that substantially improves the QIC performance. Extensive simulation studies indicate that the CIC has remarkable improvement in selecting the correct correlation structures. We also illustrate our findings using a data set from the Madras Longitudinal Schizophrenia Study.
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We consider the analysis of longitudinal data when the covariance function is modeled by additional parameters to the mean parameters. In general, inconsistent estimators of the covariance (variance/correlation) parameters will be produced when the "working" correlation matrix is misspecified, which may result in great loss of efficiency of the mean parameter estimators (albeit the consistency is preserved). We consider using different "Working" correlation models for the variance and the mean parameters. In particular, we find that an independence working model should be used for estimating the variance parameters to ensure their consistency in case the correlation structure is misspecified. The designated "working" correlation matrices should be used for estimating the mean and the correlation parameters to attain high efficiency for estimating the mean parameters. Simulation studies indicate that the proposed algorithm performs very well. We also applied different estimation procedures to a data set from a clinical trial for illustration.